Sequential isolation of metabolites, RNA, DNA, and proteins from the same unique sample

Abstract

In microbial ecology, high-resolution molecular approaches are essential for characterizing the vast organismal and functional diversity and understanding the interaction of microbial communities with biotic and abiotic environmental factors. Integrated omics, comprising genomics, transcriptomics, proteomics, and metabolomics allows conclusive links to be drawn between genetic potential and function. However, this requires truly systematic measurements. In this chapter, we first assess the levels of heterogeneity within mixed microbial communities, thereby demonstrating the need for analyzing biomolecular fractions obtained from a single and undivided sample to facilitate multi-omic analysis and meaningful data integration. Further, we describe a methodological workflow for the reproducible isolation of concomitant metabolites, RNA (optionally split into large and small RNA fractions), DNA, and proteins. Depending on the nature of the sample, the methodology comprises different (pre)processing and preservation steps. If possible, extracellular polar and nonpolar metabolites may first be extracted from cell supernatants using organic solvents. Cells are homogenized by cryomilling before small molecules are extracted with organic solvents. After cell lysis, nucleic acids and protein fractions are sequentially isolated using chromatographic spin columns. To prove the broad applicability of the methodology, we applied it to microbial consortia of biotechnological (biological wastewater treatment biomass), environmental (freshwater planktonic communities), and biomedical (human fecal sample) research interest. The methodological framework should be applicable to other microbial communities as well as other biological samples with a minimum of tailoring and represents an important first step in standardization for the emerging field of Molecular Eco-Systems Biology.

Keywords: Biomolecular isolation; Eco-Systems Biology; Integrated omics; Microbial community; Multi-omics; Sample heterogeneity.